Benefits and limits of quality cost concept applied to software industry

Quality Cost approach is important to be implemented for each product or project of any software company, wherever it’s possible, because it provides additional and more accurate information about costs, costs determined by level of product/project quality. In order to minimize the costs of the required quality level in software industry is important to find out a balance between prevention costs and failure costs. But, even if the prevention costs are very high, it doesn’t assure the elimination of all quality problems or it finally drives the product/project to an unacceptable price from the consumer point of view.failure costs, prevention costs, quality cost, software industry.

Measuring the Impact of Quality Improvement in a Software Company

The quality issue is not only a matter of developing and implementing a quality system. It mandatory this system to function precisely on a long term basis. The evaluation of quality impact as a consequence of its improvement is a scary thing the quality specialists prefer to be apart due to its complexity. That’s the reason why the article emphasize on: the need and justification of quality impact evaluation, particularities of quality in software domain generated by its specificity, what evaluation of economic effects means in the context of a quality improvement particularly in a software company, a proposed method to calculate the impact of quality (on the costs structure), a practical example of how the method should be used and the results interpreted based on two simulated case.quality improvement; quality management; software industry; quality impact evaluation; measure quality.

Open Source Software, Competition and Potential Entry

We analyze a model with two software firms, quality improving coding expenditures and potential competition. The firms can publish parts of their software as open source. Publishing software implies positive spillovers and thus reduces the firms' coding costs. On the other hand there exist two negative effects. First, lower coding costs induce higher coding expenditures which decreases the firms' profits if their programs are substitutes. Second, open source encourages entry and increases the expenditures required to deter entry. The firms' optimal open source decisions balance these opposite effects.Open Source, Spillovers, Potential Entry

Maintenance of Automated Test Suites in Industry: An Empirical study on Visual GUI Testing

Context: Verification and validation (V&V) activities make up 20 to 50 percent of the total development costs of a software system in practice. Test automation is proposed to lower these V&V costs but available research only provides limited empirical data from industrial practice about the maintenance costs of automated tests and what factors affect these costs. In particular, these costs and factors are unknown for automated GUI-based testing. Objective: This paper addresses this lack of knowledge through analysis of the costs and factors associated with the maintenance of automated GUI-based tests in industrial practice. Method: An empirical study at two companies, Siemens and Saab, is reported where interviews about, and empirical work with, Visual GUI Testing is performed to acquire data about the technique's maintenance costs and feasibility. Results: 13 factors are observed that affect maintenance, e.g. tester knowledge/experience and test case complexity. Further, statistical analysis shows that developing new test scripts is costlier than maintenance but also that frequent maintenance is less costly than infrequent, big bang maintenance. In addition a cost model, based on previous work, is presented that estimates the time to positive return on investment (ROI) of test automation compared to manual testing. Conclusions: It is concluded that test automation can lower overall software development costs of a project whilst also having positive effects on software quality. However, maintenance costs can still be considerable and the less time a company currently spends on manual testing, the more time is required before positive, economic, ROI is reached after automation

A project management quality cost information system for the construction industry

A prototype Project Management Quality Cost System (PROMQACS) was developed to determine quality costs in construction projects. The structure and information requirements that are needed to provide a classification system of quality costs were identified and discussed. The developed system was tested and implemented in two case study construction projects to determine the information and management issues needed to develop PROMQACS into a software program. In addition, the system was used to determine the cost and causes of rework that occurred in the projects. It is suggested that project participants can use the information in PROMQACS to identify shortcomings in their project-related activities and therefore take the appropriate action to improve their management practices in future projects. The benefits and limitations of PROMQACS are identified

Semantic annotation, publication, and discovery of Java software components: an integrated approach

Component-based software development has matured into standard practice in software engineering. Among the advantages of reusing software modules are lower costs, faster development, more manageable code, increased productivity, and improved software quality. As the number of available software components has grown, so has the need for effective component search and retrieval. Traditional search approaches, such as keyword matching, have proved ineffective when applied to software components. Applying a semantically- enhanced approach to component classification, publication, and discovery can greatly increase the efficiency of searching and retrieving software components. This has been already applied in the context of Web technologies, and Web services in particular, in the frame of Semantic Web Services research. This paper examines the similarities between software components and Web services and adapts an existing Semantic Web Service publication and discovery solution into a software component annotation and discovery tool which is implemented as an Eclipse plug-in

A General Approach of Quality Cost Management Suitable for Effective Implementation in Software Systems

Investments in quality are best quantified by implementing and managing quality cost systems. A review of various opinions coming from practitioners and researchers about the existent quality cost models reveals a set of drawbacks (e.g. too theoretical and too close to ideal cases; too academic, with less practical impact; too much personalized to particular business processes, with difficulties in extrapolating to other cases; not comprising all dimensions of a business system). Using concepts and tools in quality management theory and practice and algorithms of innovative problem solving, this paper formulates a novel approach to improve practical usability, comprehensiveness, flexibility and customizability of a quality cost management system (QCMS) when implementing it in a specific software application. Conclusions arising from the implementation in real industrial cases are also highlighted.Quality Costs, Performance Planning and Monitoring, Quality Management, Quality Cost Software

What to Fix? Distinguishing between design and non-design rules in automated tools

Technical debt---design shortcuts taken to optimize for delivery speed---is a critical part of long-term software costs. Consequently, automatically detecting technical debt is a high priority for software practitioners. Software quality tool vendors have responded to this need by positioning their tools to detect and manage technical debt. While these tools bundle a number of rules, it is hard for users to understand which rules identify design issues, as opposed to syntactic quality. This is important, since previous studies have revealed the most significant technical debt is related to design issues. Other research has focused on comparing these tools on open source projects, but these comparisons have not looked at whether the rules were relevant to design. We conducted an empirical study using a structured categorization approach, and manually classify 466 software quality rules from three industry tools---CAST, SonarQube, and NDepend. We found that most of these rules were easily labeled as either not design (55%) or design (19%). The remainder (26%) resulted in disagreements among the labelers. Our results are a first step in formalizing a definition of a design rule, in order to support automatic detection.Comment: Long version of accepted short paper at International Conference on Software Architecture 2017 (Gothenburg, SE